Search Results for "ai"
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Showing 101 open source projects for "ai"
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1
Ollama
Run models like Kimi-K2.5, GLM-5, DeepSeek, gpt-oss, Gemma, Qwen etc.
...Overall, Ollama focuses on privacy, local-first AI execution, and developer-friendly tooling for building with open models. -
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llama.cpp
Port of Facebook's LLaMA model in C/C++
The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments. -
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TEN Framework
TEN, a voice agent framework to create conversational AI.
TEN (Transformative Extensions Network) is a voice agent framework for creating conversational AI applications, focusing on high performance and modularity. -
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MimiClaw
Run OpenClaw on a $5 chip
MimiClaw (from the mimiclaw project) is an edge-AI personal assistant that runs directly on extremely low-cost hardware like an ESP32-S3 microcontroller without a full operating system, Node.js, or cloud backend. By running pure C on a bare-metal chip, MimiClaw brings AI interactions and persistent memory to a tiny USB-powered device you can carry in your pocket. You connect the device to Wi-Fi and chat with it using Telegram, making it a convenient always-on assistant for tasks like reminders, quick lookups, or custom AI interactions. ... -
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codebase-memory-mcp
High-performance code intelligence MCP server
codebase-memory-mcp is a high-performance code intelligence MCP server built for AI coding agents. It indexes codebases into a persistent knowledge graph so agents can understand architecture, symbols, call chains, routes, and cross-service relationships without reading every file repeatedly. The project uses tree-sitter AST analysis across 158 languages and adds Hybrid LSP type resolution for major languages like Python, TypeScript, JavaScript, Go, C#, Java, Rust, C, and C++. ... -
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TuyaOpen
Next-gen AI+IoT framework for T2/T3/T5AI/ESP32/and more
TuyaOpen is an open-source AI-enabled Internet of Things development framework designed to simplify the creation and deployment of smart connected devices. The platform provides a cross-platform C and C++ software development kit that supports a wide range of hardware platforms including Tuya microcontrollers, ESP32 boards, Raspberry Pi devices, and other embedded systems. -
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zclaw
Your personal AI assistant at all-in 888KiB
zclaw is a highly compact personal AI assistant framework designed to run on constrained embedded hardware such as the ESP32. The project focuses on delivering core assistant capabilities within an extremely small footprint, demonstrating how AI-driven automation can operate on microcontrollers. It includes support for GPIO control, scheduled tasks, memory handling, and other embedded automation features that enable real-world device interaction. -
8
LearnOpenCV
C++ and Python Examples
...The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. Many examples integrate popular frameworks like PyTorch, OpenCV, and ONNX to reflect modern AI workflows. Overall, LearnOpenCV functions as a comprehensive applied learning hub for developers building expertise in computer vision and AI. -
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WanGP
AI video generator optimized for low VRAM and older GPUs use
Wan2GP is an open source AI video generation toolkit designed to make modern generative models accessible on consumer-grade hardware with limited GPU memory. It acts as a unified interface for running multiple video, image, and audio generation models, including Wan-based models as well as other systems like Hunyuan Video, Flux, and Qwen. A key focus of the project is reducing VRAM requirements, enabling some workflows to run on as little as 6 GB while still supporting older Nvidia and certain AMD GPUs. ... -
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10
TEN
Open-source framework for conversational voice AI agents
TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. ... -
11
Clawdmeter
ESP32 desk dashboard that shows Claude Code usage
...The board’s side buttons can also send keyboard shortcuts for Claude Code voice mode and mode toggling through BLE HID. Clawdmeter is best suited for Claude Code power users who want a physical, ambient view of their AI tool consumption. -
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FLUX.2-klein-4B
Flux 2 image generation model pure C inference
FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. Because... -
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Cactus
Low-latency AI inference engine optimized for mobile devices
...It supports a wide range of AI tasks including text generation, speech-to-text, vision processing, and retrieval-augmented workflows through a unified API interface. A notable feature of Cactus is its hybrid execution model, which can dynamically route tasks between on-device processing and cloud services when additional compute is required. -
14
Colibrì
Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine
Colibri is a compact inference engine designed to run the 744-billion-parameter GLM-5.2 mixture-of-experts model on consumer hardware. It keeps the dense portion of the quantized model in memory while streaming routed experts from a large disk-based store as they are needed. The runtime is implemented in pure C, requires no Python or BLAS during inference, and can operate without a GPU. Compressed attention caches, expert caching, optional hot tiers, and speculative decoding reduce memory... -
15
PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
...The runtime is capable of running language models with billions of parameters on devices with only a few hundred megabytes of memory, which is significantly lower than typical LLM infrastructure requirements. This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources. -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
Seamless Communication is a research project focused on building more integrated, low-latency multimodal communication between humans and AI agents. The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak, gesture, point) or query, and a cross-modal reasoning layer that fuses perception with semantic context. ... -
17
AI File Sorter
Local AI file organization with categorization and rename suggestions
AI File Sorter is a cross-platform desktop application that uses AI (local LLMs run on your computer) to organize files and suggest meaningful file names based on real content, not just filenames or extensions. The app can analyze images locally and propose descriptive rename suggestions (for example, IMG_2048.jpg → clouds_over_lake.jpg). -
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fairseq2
FAIR Sequence Modeling Toolkit 2
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. -
19
Databend
Cloud-native open source data warehouse for analytics and AI queries
...Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
20
ds4.c
DeepSeek 4 Flash local inference engine for Metal
...Built as a native low-level implementation, it focuses on performance, reduced abstraction overhead, and direct integration with Apple GPU acceleration through Metal compute graphs. The project also supports streaming inference behavior and local API serving for integration with external tools and AI applications. Overall, ds4 represents a minimalist high-performance approach to running large language models locally without relying on heavyweight inference frameworks. -
21
LLMFarm
llama and other large language models on iOS and MacOS offline
...It emphasizes modularity, allowing users to integrate different models, backends, or tools depending on their needs and hardware capabilities. LLMFarm is particularly useful for developers and researchers experimenting with local AI systems, as it lowers the barrier to entry for running and testing models without extensive setup. It also supports optimization techniques to improve performance on limited hardware, making it viable for smaller-scale deployments. -
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Logic Programming and Deductive Database system (Tabled Prolog) for Unix, Mac, and Windows.
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SynaptaOS
Synapta OS is a preconfigured educational Linux distribution with AI
🌐 Synapta OS Synapta OS is an educational Linux distribution preconfigured with local Artificial Intelligence (AI) capabilities. It is designed for schools and remote areas where Internet connectivity is limited or unavailable, offering access to AI-based learning and digital tools offline. Version 1.4.6 -
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Amoeba
Linux Command Line Learning Program
Amoeba is a Linux command-line learning program that observes and adapts to the Linux command line storing learned strings and their usage data. It enhances command-line proficiency by capturing command outputs, adapting string lengths, and periodically saving knowledge. Sandboxing is essential for security, and optionally a virtual machine would further isolates it from the host system. Contributions and improvements are encouraged via the GitHub repository. -
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Recast Navigation
Navigation mesh generation and pathfinding toolkit for game AI systems
Recast Navigation is an open source toolkit designed for building navigation meshes and performing pathfinding in 3D environments, particularly for video games and simulations. It provides a set of libraries that transform input geometry into navigation meshes that AI agents can use to move through virtual worlds. Its core component, Recast, constructs navigation meshes by rasterizing triangle meshes into voxels, filtering out areas that are not walkable, and converting the remaining regions into polygon meshes suitable for navigation. Detour complements this system by providing runtime pathfinding, spatial queries, and navigation utilities that allow agents to move efficiently across the generated mesh. ...
